Rusch T, Mair P (2025). stops: Structure Optimized Proximity Scaling. doi:10.32614/CRAN.package.stops, R package version 1.9-1, https://CRAN.R-project.org/package=stops.

If stops() or c-structuredness indices are used, please cite:

Rusch T, Mair P, Hornik K (2023). “Structure-based hyperparameter selection with Bayesian optimization in multidimensional scaling.” Statistics and Computing, 33(28), 1-18. doi:10.1007/s11222-022-10197-w.

If powerStressMin() is used, please cite:

de Leeuw J, Groenen P, Mair P (2016). “Minimizing rstress using nested majorization.” UCLA. https://rpubs.com/deleeuw/142619.

If bcStressMin() is used, please cite:

Chen L, Buja A (2013). “Stress functions for nonlinear dimension reduction, proximity analysis, and graph drawing.” Journal of Machine Learning Research, 14, 1145-1173.

If lmds() is used, please cite:

Chen L, Buja A (2009). “Local multidimensional scaling for nonlinear dimension reduction, graph drawing, and proximity analysis.” Journal of the American Statistical Association, 104, 209-219.

Corresponding BibTeX entries:

  @Manual{,
    title = {stops: Structure Optimized Proximity Scaling},
    author = {Thomas Rusch and Patrick Mair},
    year = {2025},
    note = {R package version 1.9-1},
    url = {https://CRAN.R-project.org/package=stops},
    doi = {10.32614/CRAN.package.stops},
  }

  @Article{,
    author = {Thomas Rusch and Patrick Mair and Kurt Hornik},
    title = {Structure-based hyperparameter selection with {B}ayesian
      optimization in multidimensional scaling},
    journal = {Statistics and Computing},
    year = {2023},
    volume = {33},
    number = {28},
    pages = {1-18},
    doi = {10.1007/s11222-022-10197-w},
  }

  @TechReport{,
    author = {Jan {de Leeuw} and Patrick Groenen and Patrick Mair},
    title = {Minimizing rstress using nested majorization},
    year = {2016},
    url = {https://rpubs.com/deleeuw/142619},
    institution = {UCLA},
  }

  @Article{,
    author = {Lisha Chen and Andreas Buja},
    title = {Stress functions for nonlinear dimension reduction,
      proximity analysis, and graph drawing.},
    journal = {Journal of Machine Learning Research},
    year = {2013},
    volume = {14},
    pages = {1145-1173},
  }

  @Article{,
    author = {Lisha Chen and Andreas Buja},
    title = {Local multidimensional scaling for nonlinear dimension
      reduction, graph drawing, and proximity analysis.},
    journal = {Journal of the American Statistical Association},
    year = {2009},
    volume = {104},
    pages = {209-219},
    year = {2009},
  }